Retail items are sold in a variety of different ways. For example, a barcode on an item to be sold is scanned by a barcode scanner and the price is looked up in a price look-up (PLU) table. A point of sale (POS) terminal builds up a list of items and prices as items are scanned and a total price and itemized receipt are generated in a known manner. Other items are sold by weight, quantity, length or the like.
As an example of items sold by weight, item price information is commonly embedded in barcodes for applications such as deli products, such as meat, cheese and the like. Alternately, the weight of an item is sometimes embedded within the item barcode for purposes of price determination. For example, red delicious apples may be $1.59 a pound and a barcode may indicate that a bag is 5 pounds so that the ultimate price is determined by multiplying 5 pounds×$1.59/pound.
A wide variety of self-checkout apparatus and solutions have been proposed and adopted over the past decade or so. See, for example, U.S. Pat. Nos. 6,286,758; 7,466,231; 7,575,162; 7,533,799; 7,620,568; 7,673,796; and 7,673,797, all of which are assigned to the assignee of the present invention and incorporated by reference herein in their entirety.
Weight checks may be employed in a variety of contexts as security checks and to prevent fraud. As one example, in a service aided checkout environment, a weight of an item may be checked to prevent a service person assisted fraud where one item is scanned and another more expensive item is bagged, a customer swapping one bar code label removed from a less expensive item for another from a more expensive item, a customer substituting a customer generated bar code, or the like.
In self-checkout, one typical self-service terminal includes security systems that monitor the operation of the terminal and the activities of the customer. For example, a security weight scale or weight scales are incorporated into the terminal to monitor the total weight of the items brought by the customer to the terminal or the total weight of the items placed in a grocery or shopping bag. In such security systems, a software routine is executed by a computer or processor associated with the terminal that analyzes the signal output from the security weight scale, as well as, other user-interfaces of the terminal. One typical software routine compares the weight of each item as it is scanned with a database of expected weight values. Any discrepancy results in the generation of an error message and a pause in the checkout routine until the customer or store personnel takes appropriate corrective action, such as re-scanning the merchandise. A weight error signal may result in intervention by store personnel to clear up the problem.
In one weight verification routine, weight signals from a security scale are verified against a weight for each scanned product where the mean weight Mn of each product or item 1 through item n available in the store is stored in a database along with a weight standard deviation SDn for each item. As an item is scanned by the scanner and placed on a scale, the weight measured at the scale is compared to a weight range calculated from the mean and standard deviation data extracted from the database for that item. If the weight falls within a calculated range Mn±the standard deviation SDn (optionally multiplied by an arbitrary constant A), the entry is accepted. If the weight falls outside this range, the entry is rejected. In the self-checkout context, the customer is instructed to re-scan and/or re-weigh the item. In addition, in some terminals, a weight error is communicated to a store attendant as part of the terminal security measures. The routine continuously updates the mean weight and standard deviation values for each item with each new accepted observation of the weight of that item.
As further described in U.S. Pat. Nos. 7,620,568 and 6,712,268 assigned to the assignee of the present application, and incorporated by reference herein in their entirety, a memory containing a weight learning database (WLDB) may be suitably employed. The WLDB contains a predetermined weight for items to be weighed and can learn the weights of each item from a series of weighings of the item. Commonly such learning systems are unable to apply security the first few times a new item is sold because the characteristic weight and variance have not been determined. When the inventory count of items is large and re-occurring week to week, the inability to provide weight characteristic checking for the first few times the item is sold is not significant.